TPDS大数据分析系统设计  

Design of TPDS Big Data Analysis System

作　　者：史晓磊 冯丽敏 蒋荟 王华伟 李源 SHI Xiaolei;FENG Limin;JIANG Hui;WANG Huawei;LI Yuan(Institute of Computing Technologies,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)

机构地区：[1]中国铁道科学研究院集团有限公司电子计算技术研究所,北京100081

出　　处：《铁道机车车辆》2022年第1期95-98,共4页Railway Locomotive & Car

基　　金：中国铁道科学研究院集团有限公司电子计算技术研究所基金项目(DZYF18-18)。

摘　　要：伴随着铁路货车大幅度提速、重载运输的快速发展,对货车安全管理、运用、检修业务提出了更高水平的要求。当前迫切需要通过对TPDS系统监测数据开展深入挖掘和规律分析工作,更加及时、有效地提供货车运行技术状态信息,为货车故障诊断与预测、货车检修提供辅助决策支撑。目前铁路车辆部门对TPDS系统历史监测数据深入挖掘研究和应用尚处于起步阶段,数据价值未最大化发挥,传统的计算技术和TPDS系统自身的处理能力已无法适应业务数据爆炸式的增长需要。当前Web服务、云计算、大数据等新一代计算机技术不断发展,并在社会各行各业都有了深入的应用,大数据技术的成功应用为TPDS系统检测数据深入挖掘提供了重要经验借鉴。Along with the rapid development of railway wagons and heavy-haul transportation, higher levels of requirements have been imposed on the safety management, operation, and maintenance of trucks. At present, it is urgent to carry out in-depth mining and regular analysis of the monitoring data of the TPDS system to provide timely and effective information on the technical status of truck operation, the in-depth research and application of historical monitoring data of the TPDS system by the railway vehicle department is still in its infancy, and the value of data has not been maximized. Traditional computing technology and the processing capacity of the TPDS system itself cannot meet the explosive growth of business data. At present, the new generation of computer technologies such as Web services, cloud computing, and big data are constantly developing, and have been deeply applied in all walks of life in society. The successful application of big data technologies has provided important lessons for in-depth mining of TPDS system inspection data.

关 键 词：安全监测 大数据 数据挖掘 

分 类 号：U272[机械工程—车辆工程]